This is where the final project report write-up goes.

Before you submit, make sure everything runs as expected.

You can add sections as you see fit. Make sure you have a section called “Introduction” at the beginning and a section called “Conclusion” at the end. The rest is up to you!

##Introduction - Load the tidyverse, ggplot, and rtweet packages

library(tidyverse)
library(ggplot2)
library(rtweet)
library(readr)

This data set was scraped from WineEnthusiast, a website that reviews and rates many differet types of wines.

wines <- read.csv(file = '../data/winemag-data-130k-v2.csv')[,-1]
set.seed(19630217)
wine_sample<- sample_n(wines, 1000)

Select the provinces based on points and Select the best province for wine based on the average points of the sample size.

#find the average number of points across the 1,000 samples

wine_per_province <- wine_sample %>% 
  select(province, points) %>% 
  summarise(points = mean(points))
wine_per_province

#Find the best province for wine using the average points across the 1,000 samples

best_province <- wine_sample %>% 
  group_by(province, points) %>% 
  filter(points > 88.669)
best_province  

Rating distribution

##Conclusion

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